• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.179-185
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• 2015

Although an accelerometer is a sensor that measures acceleration, it cannot be used by itself to measure the acceleration when the orientation of the sensor changes. This paper introduces a Kalman filter for the estimation of a sensor acceleration based on a six-axis inertial sensor (i.e., a three-axis accelerometer and three-axis gyroscope). The novelty of the proposed Kalman filter lies in the fact that its state vector includes not only the tilt angle variable but also the sensor acceleration. Thus, the filter can explicitly estimate the latter with a high accuracy. The accuracy of acceleration estimates were validated experimentally under three different dynamic conditions, using an optical motion capture system. It could be concluded that the performance of the proposed Kalman filter was comparable to that of the state-of-the-art estimation algorithm employed by the Xsens MTw. The proposed algorithm may be more suitable than inertial/magnetic sensor-based algorithms for various applications adopting six-axis inertial sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.431-432
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• 2018

Humans have used acceleration sensors to perceive behavior. Using the application principles of inertia sensor such as acceleration and gyro sensors, the sensor indirectly measures movement through forces applied on a three-dimensional axis. This may result in different results depending on the location of the sensor in possession, even in the same way. The sensor, which is also mounted on popular smartphones, measured different values of acceleration sensors, whether in hand or in pocket, which are commonly used by people.

• Journal of Sensor Science and Technology
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• v.21 no.3
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• pp.198-203
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• 2012

In this paper, the driving information system of the bicycle has been studied by using the 3-axis acceleration sensor. The sensor module composed of 3-axis acceleration sensor and MCU(Microcontroller Unit) was mounted onto the handle of bicycle and the experiments were conducted on the flatland, uphill and downhill of bicycle road. Three axis acceleration values were converted to the pitch and roll angles, then four major compensation methods have been applied to achieve meaningful data for driving information system. The experimental results of pitch angles showed 2.46, -1.26, 7.79 degrees in case of flatland, uphill, downhill, respectively. When the steering handle turned to the left direction, roll angles showed -29.35, -41.67, -36.98 degrees at each road condition. With the right-turn, roll angles presented 20.05, 33.75, 24.44 degrees in case of flatland, uphill, and downhill, respectively. The pitch angle has been increased more than 40 degrees at stop mode. By using the change of pitch and roll angles, we could obtain the driving information system of bicycle successfully.

• Journal of Korean Association for Spatial Structures
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• v.16 no.1
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• pp.85-94
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• 2016

In this study, an acceleration sensor that has optical fibers to measure the inclination and acceleration of a structure through contradictory changes in two-component FBG sensors was examined. The proposed method was to ensure precise measurement through the unification of the deformation rate sensor and the angular displacement sensor. A high sensitivity three-axis accelerometer was designed and prepared using this method. To verify the accuracy of the accelerometer, the change in wavelength according to temperature and tension was tested. Then, the change in wavelength of the prepared accelerometer according to the sensor angle, and that of the sensor according to the change in ambient temperature were measured. According to the test results on the FBG-based vibration sensor that was developed using a high-speed vibrator, the range in measurement was 0.7 g or more, wavelength sensitivity, 2150 pm/g or more, and the change in wavelength change, $9.5pm/^{\circ}C$.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1761-1766
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• 2008

This paper deals with a novel autocalibration method of three-axis micromachined accelerometers applied to a new golf swing diagnosis equipment for golfers. This diagnosis equipment can help golfers monitor and anlalyze their swing posture and therefore modify their swing action to get better score and enjoy their lives through golf. The micromachined accelerometers to get information of the motion are the essential part of the putting club to measure the three-axis acceleration as accurately as possible. This paper presents an efficient autocalibration algorithm to find the offset and sensitivity of accelerometers by only using the static measurement data at six different positions. The experimetnal results on the developed putters show the validity of the proposed algorithm for the new smart putter.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.71-75
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• 2019

Sleep apnea is a disease that causes various complications, and the polysomnography is expensive and difficult to measure. The purpose of this study is to develop an unrestricted wearable monitoring system so that patients can be examined in a familiar environment. We used a method to detect sleep apnea events and to determine sleep satisfaction by non-constrained method using SpO2 measurement sensor and 3-axis acceleration sensor. Heart rate and SpO2 were measured at the finger using max30100. After acquiring the SpO2 data of the user in real time, the apnea measurement algorithm was used to transmit the number of apnea events of the user to the mobile phone using Bluetooth (HC-06) on the wrist. Using the three-axis acceleration sensor (mpu6050) attached to the upper body, the number of times of tossing and turning during sleep was measured. Based on this data, this algorithm evaluates the patient's tossing and turning during sleep and transmits the data to the mobile phone via Bluetooth. The power source used 9 volts battery to operate Arduino UNO and sensors for portability and stability, and the data received from each sensor can be used to check the various degree between sleep apnea and sleep tossing and turning on the mobile phone. Through thisstudy, we have developed a wearable sleep apnea measurement system that can be easily used at home for the problem of low sleep efficiency of sleep apnea patients.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.565-574
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• 2015

Falls are the main cause of serious injuries and accidental deaths in people over the age of 65. Due to widespread adoption of smartphones, there has been a growing interest in the use of smartphones for detecting human behavior and activities. Modern smartphones are equipped with a wide variety of sensors such as an accelerometer, a gyroscope, camera, GPS, digital compass and microphone. In this paper, we introduce a new method that determines the fall direction of human subjects by analyzing the three axis components of acceleration vector.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1167-1172
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• 2015

This paper describes the implementation of wearable AHRS for an electromagnetic motion capture system that can trace and analyze human motion on the principal nine axes of inertial sensors. The module provides a three-dimensional (3D) attitude and heading angles combining MEMS gyroscopes, accelerometers, and magnetometers based on the extended Kalman filter, and transmits the motion data to the 3D simulation via Wi-Fi to realize the unrestrained movement in open spaces. In particular, the accelerometer in AHRS is supposed to measure only the acceleration of gravity, but when a sensor moves with an external linear acceleration, the estimated linear acceleration could compensate the accelerometer data in order to improve the precision of measuring gravity direction. In addition, when an AHRS is attached in an arbitrary position of the human body, the compensation of the axis of rotation could improve the accuracy of the motion capture system.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.469-475
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• 2015

This paper describes about the method for designing an extended Kalman filter to accurately measure the position of the spatial-phase system using a semiconductor sensor. Spatial position is expressed by the correlation of the rotated coordinate system attached to the body from the inertia coordinate system (a fixed coordinate system). To express the attitude, quaternion was adapted as a state variable, Then, the state changes were estimated from the input value which was measured in the gyro sensor. The observed data is the value obtained from the acceleration sensor. By matching between the measured value in the acceleration sensor and the predicted calculation value, the best variable was obtained. To increase the accuracy of estimation, designation of the extended Kalman filter was performed, which showed excellent ability to adjust the estimation period relative to the sensor property. As a result, when a three-axis gyro sensor and a three-axis acceleration sensor were adapted in the estimator, the RMS(Root Mean Square) estimation error in simulation was retained less than 1.7[$^{\circ}$], and the estimator displayed good property on the prediction of the state in 100 ms measurement period.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.4
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• pp.408-415
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• 2016

The vehicle attitude and sideslip is critical information to control the vehicle to prevent from unintended motion. Many of estimation strategy use bicycle model or IMU integration, but both of them have limits on application. The main purpose of this paper is development of vehicle orientation estimator which is robust to various vehicle state and road shape. The suggested estimator use 3-axis magnetometer, yaw rate sensor and lateral acceleration sensor to estimate three Euler angles of vehicle. The estimator is composed of two individual observers: First, comparing the known magnetic field and gravity with measured value, the TRIAD algorithm calculates optimal rotational matrix when vehicle is in static or quasi-static condition. Next, merging 3-axis magnetometer with inertial sensors, the extended Kalman filter is used to estimate vehicle orientation under dynamic condition. A validation through simulation tools, Carsim and Simulink, is performed and the results show the feasibility of the suggested estimation method.